4.6 Article

Fast estimation of the enthalpy-temperature function of Phase Change Materials

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.expthermflusci.2020.110317

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Phase Change Material; Thermodynamic characterization; Enthalpy-temperature function; Inverse method

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This paper introduces a method for rapidly estimating the enthalpy-temperature function of Phase Change Materials (PCMs) using a simple experimental setup and reliable mathematical algorithm. The accuracy of the method was validated using distilled water as a reference PCM, showing good results. Additionally, the method was proven effective for PCMs undergoing progressive melting.
This paper presents a method for fast estimation of the enthalpy-temperature function of Phase Change Materials (PCMs). The method combines a simple experimental setup with a non-iterative, reliable mathematical algorithm that allows retrieving the enthalpy-temperature function from measurements of heat flux and temperature at a single point. Distilled water was used as reference PCM for validation purposes because its enthalpy function is known with high accuracy. Moreover, water is characterized by sharp melting/solidification processes and very high enthalpy of melting, which is challenging for the estimation method proposed. The results achieved show quite good accuracy in the determination of melting point (+/- 0.06 degrees C), latent heat of melting (+/- 1.5%) and specific heats (+/- 5 - 8%). To prove that the estimation method also works with PCMs undergoing progressive instead of sharp melting, a composite material made of a graphite-foam enclosing a solid-solid PCM was also tested. Finally, the potential interest of the method for identifying and diagnosing PCM degradation in thermal cycling tests was shown by testing a PCM with leakage problems. Compared to Differential Scanning Calorimeter (DSC) in step-scan mode, which is the reference method for determining the enthalpy-temperature function of a PCM, our method shows comparable accuracy while providing significant advantages, such as short testing time (less than 2 h instead of days) and low-cost experimental equipment. The proposed method could hence be of great value to accelerate PCMs development and benchmark, as well as for databases building-up.

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